scholarly journals Multi-lidar wind resource mapping in complex terrain

2020 ◽  
Vol 5 (3) ◽  
pp. 1059-1073 ◽  
Author(s):  
Robert Menke ◽  
Nikola Vasiljević ◽  
Johannes Wagner ◽  
Steven P. Oncley ◽  
Jakob Mann
Keyword(s):  
Complex Terrain ◽  
Forest Canopy ◽  
Ground Level ◽  
Surface Drag ◽  
Flow Models ◽  
Wind Speeds ◽  
Eddy Simulation ◽  
Lidar Measurements ◽  
Wind Resource ◽  
Wind Resources

Abstract. Scanning Doppler lidars have great potential for reducing uncertainty of wind resource estimation in complex terrain. Due to their scanning capabilities, they can measure at multiple locations over large areas. We demonstrate this ability with dual-Doppler lidar measurements of flow over two parallel ridges. The data have been collected using two pairs of scanning lidars operated in a dual-Doppler mode during the Perdigão 2017 measurement campaign. There the scanning lidars mapped the flow 80 m above ground level along two ridges, which are considered favorable for wind turbine siting. The measurements are validated with sonic wind measurements at each ridge. By analyzing the collected data, we found that wind speeds are on average 10 % higher over the southwest ridge compared to the northeast ridge. At the southwest ridge, the data show, for approach flow normal to the ridge, a change of 20 % in wind speed along the ridge. Fine differences like these are difficult to reproduce with computational flow models, as we demonstrate by comparing the lidar measurements with Weather Research and Forecasting large-eddy simulation (WRF-LES) results. For the measurement period, we have simulated the flow over the site using WRF-LES to compare how well the model can capture wind resources along the ridges. We used two model configurations. In the first configuration, surface drag is based purely on aerodynamic roughness, whereas in the second configuration forest canopy drag is also considered. We found that simulated winds are underestimated in WRF-LES runs with forest drag due to an unrealistic forest distribution on the ridge tops. The correlation of simulated and observed winds is, however, improved when the forest parameterization is applied. WRF-LES results without forest drag overestimated the wind resources over the southwest and northeast ridges by 6.5 % and 4.5 %, respectively. Overall, this study demonstrates the ability of scanning lidars to map wind resources in complex terrain.

scholarly journals Multi-lidar wind resource mapping in complex terrain

2019 ◽  
Author(s):  
Robert Menke ◽  
Nikola Vasiljević ◽  
Johannes Wagner ◽  
Steven P. Oncley ◽  
Jakob Mann
Keyword(s):  
Complex Terrain ◽  
Forest Canopy ◽  
Ground Level ◽  
Atmospheric Conditions ◽  
Surface Drag ◽  
Wind Speeds ◽  
Forest Distribution ◽  
Aerodynamic Roughness ◽  
Wind Resource ◽  
Wind Resources

Abstract. Scanning Doppler lidars have great potential for reducing uncertainty of wind resource estimation in complex terrain. Due to their scanning capabilities, they can measure at multiple locations over large areas. We demonstrate this ability using dual-Doppler lidar measurements of flow over two parallel ridges. The data have been collected using two pairs of long-range WindScanner systems operated in a dual-Doppler mode during the Perdigão 2017 measurement campaign. The lidars mapped the flow along the southwest and northeast ridges 80 m above ground level. By analyzing the collected data, we found that for different flow conditions on average wind speeds are 10 % higher over the southwest ridge compared to the northeast ridge. At the southwest ridge, the data shows, depending on the atmospheric conditions, a change of 20 % in wind speed along the ridge. For the measurement period, we have simulated the flow over the site using WRF-LES to compare how well the model can capture wind resources along the ridges. We used two model configurations. In the first configuration, surface drag is based purely on aerodynamic roughness whereas in the second configuration forest canopy drag is also considered. We found that simulated winds are underestimated in WRF-LES runs with forest drag due to an unrealistic forest distribution on the ridge tops. The correlation of simulated and observed winds is, however, improved when the forest parameterization is applied. WRF-LES results without forest drag overestimated the wind resources over the southwest and northeast ridges by 6.5 % and 4.5 % respectively. Overall, this study demonstrates the ability of scanning lidars to map wind resources in complex terrain.

scholarly journals Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3280
Author(s):  
Julia Gottschall ◽  
Alkistis Papetta ◽  
Hassan Kassem ◽  
Paul Julian Meyer ◽  
Linda Schrempf ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Numerical Models ◽  
Numerical Data ◽  
Resource Assessment ◽  
Flow Models ◽  
Wind Speeds ◽  
Starting Point ◽  
Scanning Lidar ◽  
Wind Lidar ◽  
Wind Resource

The planning and realization of wind energy projects requires an as accurate and precise wind resource estimation as possible. Standard procedures combine shorter on-site measurements with the application of numerical models. The uncertainties of the numerical data generated from these models are, particularly in complex onshore terrain, not just rather high but typically not well quantified. In this article we propose a methodology for using a single scanning Doppler wind lidar device to calibrate the output data of a numerical flow model and with this not just quantify but potentially also reduce the uncertainties of the final wind resource estimate. The scanning lidar is configured to perform Plan Position Indicator (PPI) scans and the numerical flow data are projected onto this geometry. Deviations of the derived from the recorded line-of-sight wind speeds are used to identify deficiencies of the model and as starting point for an improvement and tuning. The developed methodology is demonstrated based on a study for a site in moderately complex terrain in central Germany and using two rather different types of numerical flow models. The findings suggest that the use of the methodology and the introduced scanning wind lidar technology offers a promising opportunity to control the uncertainty of the applied flow models, which can otherwise only be estimated very roughly.

The Application of the Micro-Siting Technique in Tioman Island, Malaysia Using the RIAM-COMPACT Software

2014 ◽  
Vol 660 ◽  
pp. 745-749
Author(s):  
Rosly Nurhayati ◽  
Mohd Sofian
Keyword(s):  
Complex Terrain ◽  
Meteorological Data ◽  
Computational Prediction ◽  
Applied Mechanics ◽  
Eddy Simulation ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Large Eddy ◽  
Asean Countries ◽  
Wind Resources

ASEAN (Association of Southeast Asian Nations) countries may have a huge potential for utilizing wind energy as it requires little in the way of land. Land in these countries is very fertile and is used by other alternatives, therefore reducing its conduciveness for developing solar energy. The wind resources map is widely available for Laos, Vietnam, Thailand, Cambodia and Philippines but there is not much information about other ASEAN countries. Based on meteorological data, Tioman Island was selected as the area that had the best potential for installing wind turbines in Malaysia. A more detailed study was conducted using a CFD model for unsteady flow, known as the Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain (RIAM-COMPACT®) which is based on the Large-Eddy Simulation (LES) technique. Micro-siting technique is used as a tool for selecting appropriate point and an inappropriate point for locating wind turbine generators (WTGs) at Tioman Island, Malaysia. The suggested points for locating WTGs were shown based on the numerical results obtained from the calculation.

scholarly journals Assessment of Resource and Forecast Modeling of Wind Speed through An Evolutionary Programming Approach for the North of Tehuantepec Isthmus (Cuauhtemotzin, Mexico)

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3197 ◽  
Author(s):  
Luis López-Manrique ◽  
E. Macias-Melo ◽  
O. May Tzuc ◽  
A. Bassam ◽  
K. Aguilar-Castro ◽  
...  
Keyword(s):  
Wind Speed ◽  
Computation Time ◽  
Ground Level ◽  
Bimodal Distribution ◽  
Programming Approach ◽  
Climatic Data ◽  
Wind Speeds ◽  
Availability Analysis ◽  
The North ◽  
Wind Resource

This work studies the characteristics of the wind resource for a location in the north zone of Tehuantepec isthmus. The study was conducted using climatic data from Cuauhtemotzin, Mexico, measured at different altitudes above the ground level. The measured data allowed establishing the profile of wind speeds as well as the analysis of its availability. Analysis results conclude that the behavior of the wind speed presents a bimodal distribution with dominant northeast wind direction (wind flow of sea–land). In addition, the area was identified as feasible for the use of low speed power wind turbines. On the other hand, the application of a new approach for very short-term wind speed forecast (10 min) applying multi-gene genetic programming and global sensitivity analysis is also presented. Using a computational methodology, an exogenous time series with fast computation time and good accuracy was developed for the forecast of the wind speed. The results presented in this work complement the panorama for the evaluation of the resource in an area recognized worldwide for its vast potential for wind power.

scholarly journals Small wind turbines study and integration in a peri-urban microgrid

2021 ◽  
Author(s):  
Paula Peña-Carro ◽  
Óscar Izquierdo-Monge ◽  
Luis Hernández-Callejo ◽  
Gonzalo Martín-Jiménez
Keyword(s):  
Wind Turbines ◽  
Urban Environments ◽  
Wind Speeds ◽  
Small Wind Turbines ◽  
Micro Power ◽  
The Cost ◽  
Wind Resource ◽  
Wind Resources ◽  
Selection Of ◽  
Instantaneous Control

The use of wind resources has always gone hand in hand with high wind speeds in open fields. This paper develops the decisions to be taken for the selection, installation, and connection of small wind turbines in peri-urban environments, where wind speeds are medium or low. The guidelines are detailed throughout the document, starting with the study of the wind resource, the selection of the turbine, installation, and real-time monitoring of production for integration into a micro power grid. The installation of small wind systems in places as close as possible to the point of demand makes it possible to achieve a reduction in the cost of the electricity bill. This is thanks to the instantaneous control of generation and demand at a particular level through the installation of software, in this case, Home Assistant. The novelty of this paper is the use of this software Home Assistant to integrate of a small wind turbine in a microgrid and its control system.

Simulation of the Scalar Transport above and within the Amazon Forest Canopy

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1631
Author(s):  
Edivaldo M. Serra-Neto ◽  
Hardiney S. Martins ◽  
Cléo Q. Dias-Júnior ◽  
Raoni A. Santana ◽  
Daiane V. Brondani ◽  
...  
Keyword(s):  
Forest Canopy ◽  
Passive Scalar ◽  
Scalar Transport ◽  
Amazon Forest ◽  
Large Eddy Simulation Model ◽  
Turbulence Structures ◽  
Wind Speeds ◽  
Eddy Simulation ◽  
Scalar Concentration ◽  
Passive Scalar Transport

The parallelized large-eddy simulation model (PALM) was used to understand better the turbulent exchanges of a passive scalar above and within a forested region located in the central Amazon. Weak (2 ms−1) and strong (6 ms−1) wind conditions were simulated. A passive scalar source was introduced to the forest floor for both simulations. The simulations reproduced the main characteristics of the turbulent flow and of the passive scalar transport between the forest and the atmosphere. Noteworthily, strong and weak wind conditions presented different turbulence structures that drove different patterns of scalar exchange both within and above the forest. These results show how passive scalar concentration is influenced by the wind speed at the canopy top. Additionally, higher wind speeds are related to stronger sweep and ejection regimes, generating more intense plumes that are able to reduce the passive scalar concentration inside the forest canopy. This work was the first that used PALM to investigate scalar transport between the Amazon rainforest and the atmosphere.

scholarly journals Evaluation of the lattice Boltzmann method for wind modelling in complex terrain

2020 ◽  
Vol 5 (4) ◽  
pp. 1507-1519
Author(s):  
Alain Schubiger ◽  
Sarah Barber ◽  
Henrik Nordborg
Keyword(s):  
Wind Energy ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Complex Terrain ◽  
Navier Stokes ◽  
Wind Flow ◽  
Ansys Fluent ◽  
Eddy Simulation ◽  
Boltzmann Method ◽  
Wind Resource

Abstract. The worldwide expansion of wind energy is making the choice of potential wind farm locations more and more difficult. This results in an increased number of wind farms being located in complex terrain, which is characterised by flow separation, turbulence and high shear. Accurate modelling of these flow features is key for wind resource assessment in the planning phase, as the exact positioning of the wind turbines has a large effect on their energy production and lifetime. Wind modelling for wind resource assessments is usually carried out with the linear model Wind Atlas Analysis and Application Program (WAsP), unless the terrain is complex, in which case Reynolds-averaged Navier–Stokes (RANS) solvers such as WindSim and Ansys Fluent are usually applied. Recent research has shown the potential advantages of large-eddy simulation (LES) for modelling the atmospheric boundary layer and thermal effects; however, LES is far too computationally expensive to be applied outside the research environment. Another promising approach is the lattice Boltzmann method (LBM), a computational fluid technique based on the Boltzmann transport equation. It is generally used to study complex phenomena such as turbulence, because it describes motion at the mesoscopic level in contrast to the macroscopic level of conventional computational fluid dynamics (CFD) approaches, which solve the Navier–Stokes (N–S) equations. Other advantages of the LBM include its efficiency; near-ideal scalability on high-performance computers (HPCs); and ability to easily automate the geometry, the mesh generation and the post-processing. However, the LBM has been applied very little to wind modelling in complex terrain for wind energy applications, mainly due to the lack of availability of easy-to-use tools as well as the lack of experience with this technique. In this paper, the capabilities of the LBM to model wind flow around complex terrain are investigated using the Palabos framework and data from a measurement campaign from the Bolund Hill experiment in Denmark. Detached-eddy simulation (DES) and LES in Ansys Fluent are used as a numerical comparison. The results show that there is in general a good agreement between simulation and experimental data, and the LBM performs better than RANS and DES. Some deviations can be observed near the ground, close to the top of the cliff and on the lee side of the hill. The computational costs of the three techniques are compared, and it has been shown that the LBM can perform up to 5 times faster than DES, even though the set-up was not optimised in this initial study. It can be summarised that the LBM has a very high potential for modelling wind flow over complex terrain accurately and at relatively low costs, compared to solving N–S equations conventionally. Further studies on other sites are ongoing.

scholarly journals The RUNE Experiment–A Database of Remote-Sensing Observations of Near-Shore Winds

2016 ◽  
Author(s):  
Rogier Floors ◽  
Alfredo Peña ◽  
Guillaume Lea ◽  
Nikola Vasiljevic ◽  
Elliot Simon ◽  
...  
Keyword(s):  
Floating Platform ◽  
Wind Speeds ◽  
Experimental Campaign ◽  
Lidar Measurements ◽  
Vertical Profiling ◽  
Near Shore ◽  
Scanning Lidar ◽  
Scanning Strategies ◽  
Wind Resource ◽  
Good Agreement

We present a comprehensive database of near-shore wind observations that were carried out during the experimental campaign of the RUNE project. RUNE aims at reducing the uncertainty of the near-shore wind resource estimates from model outputs by using lidar, ocean, and satellite observations. Here we concentrate in describing the lidar measurements. The campaign was conducted from November 2015 to February 2016 at the west coast of Denmark and comprises measurements from eight lidars, an ocean buoy and three types of satellites. The wind speed was  estimated based on measurements from a scanning lidar performing PPIs, two scanning lidars performing dual synchronized scans, and five vertical profiling lidars, of which one was operating offshore on a floating platform. The availability of measurements is highest for the profiling lidars, followed by the lidar performing PPIs, those peforming the dual setup, and the lidar buoy. Analysis of the lidar measurements reveals good agreement between the estimated 10-m wind speeds, although the instruments used different scanning strategies and measured different volumes in the atmosphere. The campaign is characterized by strong westerlies with occasional storms.

scholarly journals Assessment of wind energy potential for Tuvalu with accurate estimation of Weibull parameters

2020 ◽  
Vol 38 (5) ◽  
pp. 1742-1773
Author(s):  
Fatonga Talama ◽  
Saiyad S Kutty ◽  
Ajal Kumar ◽  
MGM Khan ◽  
M Rafiuddin Ahmed
Keyword(s):  
Maximum Likelihood ◽  
Wind Power ◽  
Power Density ◽  
Maximum Likelihood Method ◽  
Ground Level ◽  
Empirical Method ◽  
Likelihood Method ◽  
Above Ground Level ◽  
Wind Speeds ◽  
Wind Resource

Wind resource assessments are carried out for two sites in Tuvalu: Funafuti and Nukufetau. The wind speeds at 34 and 20 m above ground level were recorded for approximately 12 months and analyzed. The averages of each site are computed as the overall, daily, monthly, annual, and seasonal averages. The overall average wind speeds for Funafuti and Nukufetau at 34 m above ground level were estimated to be 6.19 and 5.36 m/s, respectively. The turbulence intensities at the two sites were also analyzed. The turbulence intensity is also computed for windy and low-wind days. Wind shear analysis was carried out and correlated with temperature variation. Ten different methods: median and quartiles method, the empirical method of Lysen, the empirical method of Justus, the moments method, the least squares method, the maximum likelihood method, the modified maximum likelihood method, the energy pattern factor method, method of multi-objective moments, and the wind atlas analysis and application program method were used to find the Weibull parameters. From these methods, the best method is used to determine the wind power density for the site. The wind power density for Funafuti is 228.18 W/m2 and for Nukufetau is 145.1 W/m2. The site maps were digitized and with the WAsP software, five potential locations were selected for each site from the wind resource map. The annual energy production for the sites was computed using wind atlas analysis and application program to be 2921.34 and 1848.49 MWh. The payback periods of installing the turbines for each site are calculated by performing an economic analysis, which showed payback periods of between 3.13 and 4.21 years for Funafuti and between 4.83 to 6.72 years for Nukufetau.

scholarly journals Towards Better Wind Resource Modeling in Complex Terrain: A k-Nearest Neighbors Approach

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4364
Author(s):  
Pedro Quiroga-Novoa ◽  
Gabriel Cuevas-Figueroa ◽  
José Luis Preciado ◽  
Rogier Floors ◽  
Alfredo Peña ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Wind Farm ◽  
Nearest Neighbor ◽  
Vertical Shear ◽  
K Nearest Neighbor ◽  
K Nearest Neighbors ◽  
Flow Models ◽  
Resource Modeling ◽  
Novel Approach ◽  
Wind Resource

Wind turbines are often placed in complex terrains, where benefits from orography-related speed up can be capitalized. However, accurately modeling the wind resource over the extended areas covered by a typical wind farm is still challenging over a flat terrain, and over a complex terrain, the challenge can be even be greater. Here, a novel approach for wind resource modeling is proposed, where a linearized flow model is combined with a machine learning approach based on the k-nearest neighbor (k-NN) method. Model predictors include combinations of distance, vertical shear exponent, a measure of the terrain complexity and speedup. The method was tested by performing cross-validations on a complex site using the measurements of five tall meteorological towers. All versions of the k-NN approach yield significant improvements over the predictions obtained using the linearized model alone; they also outperform the predictions of non-linear flow models. The new method improves the capabilities of current wind resource modeling approaches, and it is easily implemented.

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